Re: Histogram normalization

*To*: mathgroup at smc.vnet.net*Subject*: [mg40012] Re: [mg40005] Histogram normalization*From*: Kyriakos Chourdakis <tuxedomoon at yahoo.com>*Date*: Sun, 16 Mar 2003 02:20:18 -0500 (EST)*Reply-to*: k.chourdakis at qmul.ac.uk*Sender*: owner-wri-mathgroup at wolfram.com

The ``smoothed histogram'' you are looking for is replicated by the nonparametric density. I think you might find the NonParametricDensity function below useful. It is a very simplified version without control over the kernels etc. but it should do the trick. The code defines the nonparametric density, creates a 500 point sample from a t_4 distribution, and plots the ``smooth histogram'' of the sample together with the t_4. (***************************************************) (* Copy into .nb *) Quit[]; << "Statistics`ContinuousDistributions`" NonParametricDensity[x_] := Module[{sx, g, gg, T, h}, sx = StandardDeviation[x]; T = Length[x]; h = (sx*1.06)/T^0.2; g = Function[{u}, (1*Plus @@ (Exp[-((u - #1)^2/(2*h^2))] & ) /@ x)/ (T*h*Sqrt[2*Pi])]; FunctionInterpolation[g[u], {u, Min[x] - 4*h, Max[x] + 4*h}]]; dist = StudentTDistribution[4]; Y = RandomArray[dist, 500]; NPf = NonParametricDensity[Y]; Plot[{PDF[dist, x], NPf[x]}, {x, -5, 5}, Frame -> True, Axes -> False, PlotStyle -> {Thickness[0.], Thickness[0.01]}]; (***************************************************) Kyriakos Kyriakos Chourdakis http://www.theponytail.net/ __________________________________________________ Do You Yahoo!? Everything you'll ever need on one web page from News and Sport to Email and Music Charts http://uk.my.yahoo.com

**Follow-Ups**:**Re: Re: Histogram normalization***From:*Dr Bob <drbob@bigfoot.com>